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Intelligent management and scheduling approach for earthquake rescue equipment based on knowledge graph
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Tianying GUO, Xiaoyang MAO**, Qijun DUAN, Di MA
China Safety Science Journal | 2024, 34(7) : 239 - 245
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China Safety Science Journal | 2024, 34(7): 239-245
Emergency technology and management
Intelligent management and scheduling approach for earthquake rescue equipment based on knowledge graph
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Tianying GUO, Xiaoyang MAO**, Qijun DUAN, Di MA
Affiliations
  • School of Design Art and Media,Nanjing University of Science and Technology,Nanjing Jiangsu 210094,China
Published: 2024-07-28 doi: 10.16265/j.cnki.issn1003-3033.2024.07.2014
Outline
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In order to assist earthquake rescue personnel in enhancing disaster response speed and adapting to diverse search and rescue needs,an intelligent management method for earthquake rescue equipment information based on a knowledge graph was proposed. Through the top-down knowledge graph construction method,earthquake rescue knowledge was first obtained from various information sources to serve as the basis for knowledge modeling. Next,a rule-based method was used to extract search and rescue knowledge,which was then integrated based on cosine similarity. The integrated knowledge was stored in the form of Resource Description Framework (RDF) triples. Subsequently,the open-source graph database Neo4j was employed to organize the triples into a visualized knowledge graph. Finally,a question-and-answer system was built based on the knowledge graph,allowing users to query the knowledge on the graph using natural language. The results indicate that the knowledge graph includes five categories of entities and relationships: disasters,secondary disasters,environmental factors,rescue needs,and rescue equipment. It facilitates quick matching of equipment based on rescue needs. The knowledge graph-based method can effectively manage and schedule rescue equipment information,improving the efficiency of the preparation phase of rescue operations.

knowledge graph  /  earthquake rescue  /  rescue equipment  /  intelligent management  /  knowledge extraction  /  knowledge fusion  /  Neo4j
Tianying GUO, Xiaoyang MAO, Qijun DUAN, Di MA. Intelligent management and scheduling approach for earthquake rescue equipment based on knowledge graph[J]. China Safety Science Journal, 2024 , 34 (7) : 239 -245 . DOI: 10.16265/j.cnki.issn1003-3033.2024.07.2014
Year 2024 volume 34 Issue 7
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doi: 10.16265/j.cnki.issn1003-3033.2024.07.2014
  • Receive Date:2024-01-10
  • Online Date:2025-07-09
  • Published:2024-07-28
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  • Received:2024-01-10
  • Revised:2024-04-20
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    School of Design Art and Media,Nanjing University of Science and Technology,Nanjing Jiangsu 210094,China
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表12种不同金属材料的力学参数

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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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